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Errors in Word Classes Categorisation-An Analytical Approach

delete2026-04-01
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PRE
AI
S
Subramaniam, Vijayaletchumy *
N
Nagaraju, Pavitira
J
Janan, Dahlia
S
Sultan, Mohamed Thariq Hameed
DOI:10.47836/pjssh.34.2.04delete
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Abstract

Abstract

En 中文
Word classes such as Nouns (KN), Verbs (KK), andAdjectives (KA) constitute fundamental elements in sentence construction, yet they remain challenging for non-native Malay learners. This study investigates the level of mastery and types of errors in word-class determination among pupils in Tamil vernacular schools, grounded in Corder s' (1973) Error Analysis Theory. Data were collected from 134 high-achieving Year 6 pupils across two SJK(T) schools and analysed using a descriptive quantitative approach through a written test on word classes. The findings reveal notable weaknesses, with 50% of pupils failing to reach the minimum proficiency level and 11.9% attaining only the minimum standard. Four primary error categories were identified: incorrect affix selection, addition or omission of letters after affixation, and misarrangement of affixes in verbs (KK) and nouns (KN). Additionally, a new type of error was also identified, namely the neglect of essential elements when determining word classes. The implications of this study highlight the need to incorporate new language skills into the Dokumen Standard Kurikulum dan Pentaksiran (DSKP) as recommended by the Curriculum Development Division, to better support pupils'mastery ofword classification. Addressing these errors is vital to ensure pupils'ability to construct grammatically accurate sentences and to scaffold the acquisition of more complex grammatical structures.
Keywords:
Affixes
language errors
meaning of the word
non-native speaker
word class determination

Journal

P
Pertanika Journal of Social Science and Humanities
IF:
0.7
Papers:
98
Citations:
976

Organization

U
universiti putra malaysia
Scholars:
3.1K
Papers: 1.2K
Citations: 0
I
International Islamic University Malaysia
Scholars:
2.6K
Papers: 2.0K
Citations: 1.9K